Evidence map›Paper›PMID 35877201›Full record

ArticleCancer research2022

Selective Cell Size MRI Differentiates Brain Tumors from Radiation Necrosis.

Sean P Devan, Xiaoyu Jiang, Guozhen Luo, Jingping Xie, James D Quirk, John A Engelbach, Hannah Harmsen, Eliot T McKinley, Jing Cui, Zhongliang Zu and 6 more

Open access · bronzeAbstract read
In one paragraph

Article in Cancer research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
2.2field-weighted citation impact, top 13% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

11 citing papers in PubMed, 18 citations in OpenAlex.

  1. Article
  2. Review
  3. Article
  4. Engineering clinical translation of OGSE diffusion MRI.Magnetic resonance in medicine · 2025
    Review
  5. Article
  6. Article
  7. Review
  8. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

16 authors at 3 institutions in 1 country.

Sean P DevanVanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, Tennessee.
Xiaoyu JiangVanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, Tennessee.
Guozhen LuoDepartment of Radiation Oncology, Vanderbilt University Medical Center, Nashville, Tennessee.
Jingping XieVanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, Tennessee.
James D QuirkMallinckrodt Institute of Radiology, Washington University, St. Louis, Missouri.ORCID 0000-0002-6118-7097
John A EngelbachMallinckrodt Institute of Radiology, Washington University, St. Louis, Missouri.
Hannah HarmsenDepartment of Pathology, Microbiology, and Immunology, Vanderbilt University Medical Center, Nashville, Tennessee.
Eliot T McKinleyDepartment of Cell and Developmental Biology, Vanderbilt University, Nashville, Tennessee.
Jing CuiVanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, Tennessee.ORCID 0000-0003-0902-8715
Zhongliang ZuVanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, Tennessee.ORCID 0000-0001-7361-7480
Albert AttiaDepartment of Radiation Oncology, Vanderbilt University Medical Center, Nashville, Tennessee.
Joel R GarbowMallinckrodt Institute of Radiology, Washington University, St. Louis, Missouri.
John C GoreVanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, Tennessee.
Colin D McKnightDepartment of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, Tennessee.ORCID 0000-0002-4386-8999
Austin N KirschnerDepartment of Radiation Oncology, Vanderbilt University Medical Center, Nashville, Tennessee.ORCID 0000-0003-3807-6900
Junzhong XuVanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, Tennessee.ORCID 0000-0001-7895-4232
Vanderbilt University Medical Center · USVanderbilt University · USMallinckrodt (United States) · US

Funding

Vanderbilt Institute for Clinical and Translational Research (VICTR) -Identifying correlates of functional immunity in SARS-CoV-2 convalescent plasmaUL1TR002243 · NCATS · VANDERBILT UNIVERSITY MEDICAL CENTER · PI Paul A. Harris, Wesley H Self · 2017 to 2026
$130.7M
Washington University Center for Cellular ImagingP30CA091842 · NCI · WASHINGTON UNIVERSITY · PI AIMEE S JAMES · 2001 to 2026
$128.0M
Vanderbilt Clinical Oncology Research Career Development ProgramK12CA090625 · NCI · VANDERBILT UNIVERSITY MEDICAL CENTER · PI Debra L. Friedman, Paula Jill Hurley · 2001 to 2026
$16.9M
MRI Diffusion in Tumors Using Oscillating GradientsR01CA109106 · NCI · VANDERBILT UNIVERSITY MEDICAL CENTER · PI XU, JUNZHONG · 2006 to 2022
$4.0M
Replacement and Upgrade of a 3T MR Scanner for ResearchS10OD021771 · OD · VANDERBILT UNIVERSITY MEDICAL CENTER · PI GORE, JOHN C · 2016 to 2016
$2.0M
Comprehensive Evaluation of OGSE DWI for Assessing Tumor Treatment ResponseR01CA173593 · NCI · VANDERBILT UNIVERSITY MEDICAL CENTER · PI GORE, JOHN C · 2013 to 2017
$1.3M
Assessment of Tumor Early Response to Treatment by Diffusion MRIK25CA168936 · NCI · VANDERBILT UNIVERSITY MEDICAL CENTER · PI XU, JUNZHONG · 2013 to 2017
$728k
Early assessment of radiation response in brain tumors using quantitative temporal diffusion spectroscopyF32CA216942 · NCI · VANDERBILT UNIVERSITY MEDICAL CENTER · PI JIANG, XIAOYU · 2017 to 2018
$77k
NCATS NIH HHS UL1 TR002243NCI NIH HHS F32 CA216942NCI NIH HHS K12 CA090625NCI NIH HHS K25 CA168936NCI NIH HHS P30 CA091842NCI NIH HHS R01 CA109106NCI NIH HHS R01 CA173593NIH HHS S10 OD021771
6 · The paper itself

Abstract

Brain metastasis is a common characteristic of late-stage lung cancers. High doses of targeted radiotherapy can control tumor growth in the brain but can also result in radiotherapy-induced necrosis. Current methods are limited for distinguishing whether new parenchymal lesions following radiotherapy are recurrent tumors or radiotherapy-induced necrosis, but the clinical management of these two classes of lesions differs significantly. Here, we developed, validated, and evaluated a new MRI technique termed selective size imaging using filters via diffusion times (SSIFT) to differentiate brain tumors from radiotherapy necrosis in the brain. This approach generates a signal filter that leverages diffusion time dependence to establish a cell size-weighted map. Computer simulations in silico, cultured cancer cells in vitro, and animals with brain tumors in vivo were used to comprehensively validate the specificity of SSIFT for detecting typical large cancer cells and the ability to differentiate brain tumors from radiotherapy necrosis. SSIFT was also implemented in patients with metastatic brain cancer and radiotherapy necrosis. SSIFT showed high correlation with mean cell sizes in the relevant range of less than 20 μm. The specificity of SSIFT for brain tumors and reduced contrast in other brain etiologies allowed SSIFT to differentiate brain tumors from peritumoral edema and radiotherapy necrosis. In conclusion, this new, cell size-based MRI method provides a unique contrast to differentiate brain tumors from other pathologies in the brain. SIGNIFICANCE: This work introduces and provides preclinical validation of a new diffusion MRI method that exploits intrinsic differences in cell sizes to distinguish brain tumors and radiotherapy necrosis.

Indexed as

Brain NeoplasmsRadiation InjuriesCell SizeDiagnosis, DifferentialHumansMagnetic Resonance ImagingNecrosisNeoplasm Recurrence, Local

Identifiers

PMID35877201
PMCPMC9532360
OpenAlexW4287509986

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.